The human brain is made up of neurons connected to one another in a complex network. It is believed that when humans learn, new connections are made or existing ones are modified. Neural networks, used in artificial intelligence (A.I.) applications, are massively parallel computing models inspired by the human brain. Such networks are typically implemented by multiple processors connected by adaptive weights. Computational neural models based on such neural networks can simulate brain conditions and provide valuable information and insight about the human brain.
Doctors who treat patients having neuropsychiatric disorders often rely on psychiatric drugs. Specific treatments and drugs exist for specific diagnostic categories of patients. For example, neuroleptics are prescribed for schizophrenia, antidepressants are administered for depression, anxiolytics for anxiety, lithium for mania, and stimulants, such as RITALIN®, for attention-deficit/hyperactivity disorder (ADHA).
Before prescribing drugs to humans, it is prudent to first test them to ensure that they are effective, or at the very least, that they are safe. The most straightforward way to test such drugs is to test them on humans. As late as the middle of the last century, for example, it was routine to test drugs on prisoners and on patients in mental asylums. In fact, the well-known antipsychotic drug chlorpromazine was discovered in this way.
Since then, testing new drugs in this way has been acknowledged as unethical. As a result, the safety and efficacy of new drugs is assessed by testing them on animal models. In the case of psychiatric drugs, this generally involves isolating an animal behavior that is thought to be analogous to a human behavior or psychiatric condition, administering the drug in question to the animal, and observing if the behavior changes. As an example, the operant conflict test in rate is thought to embody behavior analogous to anxiety in humans and the medication DIAZEPAM®, also known as VALIUM®, was discovered by its ability to decrease such behavior in rats in a laboratory environment.
However, not all psychiatric disorders and neuropsychiatric conditions have clear behavioral correlates in animals. For certain neuropsychiatric brain disorders, such as schizophrenia, it is difficult to test the efficacy of a potential drug preclinically, in part because there are presently no well-established animal models of schizophrenia. As a result, using animal models to screen antipsychotic medications for antischizophrenic potency is not feasible. Thus, for many neurologican disorders, there are currently no well-understood and established methods for preclinically screening potential drugs safely and expeditiously.